Data Engineer – Python/AI
Bank of America
- Location
- Charlotte
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 278 approvals (FY2023)
- Posted
- Aug 24, 2026
Skills
About this role
Job Description
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Description
This job is responsible for developing and delivering data solutions to accomplish technology and business goals and initiatives. Key responsibilities include performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems. Job expectations include working with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains. Join a high‑impact technology team within Global Commercial Lending , focused on transforming core lending and payments BAU processes through AI, ML, and Generative AI solutions . This role offers a unique opportunity to design and productionize AI‑driven capabilities that deliver measurable efficiency gains , improved operational resilience, and smarter decisioning across large‑scale enterprise lending platforms. You will work closely with product, operations, and engineering teams to build, deploy, and scale ML and GenAI solutions embedded into mission‑critical platforms, while adhering to enterprise standards for security, compliance, and model governance . This position is responsible for designing, building, and operating AI/ML solutions end‑to‑end , with strong emphasis on MLOps, ML lifecycle management, and production readiness .
Responsibilities
Works across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle Leverages architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria Builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defines and builds data pipelines and complex data sets to enable data-informed decision making, identifying and raising risks at all stages of the data engineering process Develops and executes test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes Drives complex information technology projects to ensure on-time delivery and adheres to team delivery and release processes Identifies,